Radiation scanning systems used in cargo imaging technology, including land, sea, or air cargo, have advanced through multiple generations. First generation radiation scanning systems include gamma-ray sources, which are used in the mobile VACIS® gamma ray imaging system, available from Science Applications International Corporation, San Diego, Calif. (“SAIC”). The mobile VACIS® includes a Co-60 or Cs-137 isotope source and an array of individual NaI detectors operating in photon counting mode, mounted to a truck. Due to safety concerns and finite detector response time, source strength is around 1 Ci. Imaging resolution, penetration and contrast sensitivity are poorer than necessary. Typical penetration is 100 mm to 150 mm steel with ˜15 mm display resolution (pixel size).
Second generation radiation scanning systems use single energy X-ray sources, such as the Varian M-series Linatrons, available from Varian Medical Systems, Inc., Palo Alto, Calif. The use of intense pulsed X-ray source and integration detectors greatly improved radiographic performance, such as resolution, penetration and contrast sensitivity. Steel penetration is over 400 mm with 3 mm resolution with an M6/Mi6 source. This allows an inspection to reveal most (two dimensional) details inside a cargo container.
Third generation scanning systems use dual-energy X-ray transmission radiography with material discrimination. In addition to superior radiographic performance, this generation of X-ray scanning systems provide pixel-by-pixel information of material classes, such as organic, inorganic, metallic and very high-Z metals. Algorithms may also be applied to smooth out material regions based on the fact that material types is not likely to change from pixel to pixel.
Fourth generation radiation scanning systems include dual-energy X-ray transmission radiography with stacked detectors and data fusion algorithms for enhanced material classification. While stacked detectors by themselves may not work well at MeV energies, they pick up material signatures at small beam path length, which complements information from dual source energies. Coupled with advanced algorithms, fourth generation radiation scanning systems can provide better material classification than the prior generations discussed above, and is useful with small beam path length as well as larger large objects.
FIG. 1 is a schematic representation of an example of a typical cargo radiography system 10. An electron accelerator 12, such as a Varian Mi6 Linatron® linear accelerator, available from Varian Medical Systems, Inc., Palo Alto, Calif., accelerates electrons from an electron source, such as an electron gun (not shown) and directs the accelerated electrons to the target 14. X-rays are produced at the target 14 and collimated by a collimator (not shown) into fan beams to image a slice of a cargo container 16. A linear detector array 18, which may have a curved profile or folded straight sections, for example, detects X-rays transmitted through the cargo container 16. A straight path from the X-ray source target 14 to each detector element of the linear detector array 18 forms a pixel in a resulting transmission image corresponding to each X-ray pulse. The linear detector array 18 records one column of pixels in a transmission image corresponding to each X-ray pulse. When the cargo container 16 moves through the fan beam (or the source-detector combination moves along the cargo container) and more image lines (columns) are detected, a complete 2-D transmission image is recorded. Each pixel contains integrated information along a beam path by a collimator (not shown) between the target 14 and each a detector element. In other words, information along each beam path is projected onto one pixel and is not recoverable from one radiographic view. With two or more radiation source energies, and optionally with stacked detectors, integrated material information along a beam path can be calculated. However, such material information is also projected along a beam path onto a pixel.
The linear detector array 18 is electrically coupled to an image processor 20, which is coupled to a display 22. The image processor 20 comprises analog-to-digital conversion and digital processing components, as is known in the art. A processing device 24, such as a computer, for example, is electrically coupled to and controls the operation of one or more of the electron accelerator 12, the linear detector array 18, a conveyor system (not shown), the image processor 20, and the display 22. One or more memory devices 26 to store a reconstruction algorithm, detected data, resulting images, etc., is also provided. Connections between the processing device 24 and of all the components are not shown, to simplify FIG. 1. The processing device 24 may be programmed to reconstruct 2-D images. The processing device 24 may provide some or all of the processing functions of the image processor 20. While one processing device 24 is shown, additional processors or computers may be provided, as well. The image processor 20, the processing device 24, and the display 22 may be arranged and connected differently. For example, the image processor 20 may be part of the processing device 24. The processing device 24 may be programmed in software and/or hardware.
FIG. 2 is a schematic representation of another example of a radiation scanning system 50, positioned to scan a cargo container 52 supported by a truck 54. A radiation source 56, a first collimator 58, a detector array 60, and a second collimator 62 are shown. The radiation source 56 comprises a source of electrons, an accelerator, and a target (not shown), as above. Radiation generated by the radiation source 56 is collimated by the first collimator 58 to form a fan beam or a cone beam. Radiation transmitted through the cargo container 52 and optionally the truck 54 are collimated by the second collimator 62 and detected by the detector array 60. The processing device 24, one or more memory devices 26, a conveyor system (not shown), the image processor 20, and the display 22 of FIG. 1 may be provided in the system 50 of FIG. 2, as well.
Conventional CT reconstruction typically requires hundreds or thousands of views. Filtered backprojection (“FBP”), or, more broadly, direct or analytic algorithms are commonly used to reconstruct CT images. Such algorithms are derived as analytic solutions to some idealized version of the actual problem to be solved. Two problem aspects that are commonly idealized are the geometry and the physics. Geometrically, most analytic algorithms assume that data are continuously sampled along an ideal arc or line. In terms of physics, most also assume an ideal X-ray imaging mechanism, such as a noise-free monochromatic infinitesimal-width pencil-beam from a point source with no scatter using perfect noise-free linear electronics, for example. Both of these assumptions are problematic.